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Record W2084117684 · doi:10.1167/10.1.3

The role of co-circularity of local elements in texture perception

2010· article· en· W2084117684 on OpenAlexafffund
Isamu Motoyoshi, F. A. A. Kingdom

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcGill University
FundersMcGill University
KeywordsOrientation (vector space)Texture (cosmology)MathematicsPerceptionArtificial intelligencePairwise comparisonPattern recognition (psychology)GeometryComputer sciencePsychologyImage (mathematics)

Abstract

fetched live from OpenAlex

The present study analyzes the effect of local pairwise orientation relations on the perception of textural structure. We have employed a new class of stochastic stimuli comprised of paired Gabor patches with a particular orientation difference (theta) and relative angular position (phi). We measured the threshold proportion of signal pairs for discriminating the target texture from a noise texture comprised of randomly oriented pairs. The results showed that observers were sensitive not only to textures containing pairs with curvilinear configurations such as lines and curves (phi = theta / 2), but also to their orthogonal configurations such as V shapes and parallels (phi = theta / 2 + 90). Both classes of configuration exhibit the property of co-circularity, a fundamental geometric feature of edges and contours in natural images. We also found higher sensitivity for textures made from orientation pairs with either large or small orientation differences. These results suggest that in addition to orientation difference, co-circularity plays a critical role in the perception of orientation-based textural structure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.161

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.350
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2010
Admission routes2
Has abstractyes

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